Friday, November 28, 2014

Analytics needs to permeate into the very fabric of organization. Although analytics is at the top to-do agenda of any
forward-thinking business today, still, most of them think analytics is one
time project, not an ongoing business capability or embedded corporate culture,
hence, their data are “floating on the surface”, not being filtered out and
abstracted into the business insight that helps making effective decisions; so
what’re the optimal level of data analytics success, and how to achieve it?

Managers
need to envision favorable futures—not dwell on the past--no matter
how elaborately presented, to impact corporate culture, analysts need to
present managers with historical perspectives that enable estimation of
favorable futures. Corporate culture can be implemented through goal, mission,
performance tracking in top down/bottom up strategic decision; then analytics-supported
problem solving and strategic change management can achieve sustainable profits.

Analytics
needs to permeate into the very fabric of organization. When
analytics becomes part of daily measurement and business action within business
teams, only then it gets into the fabric of an organization. It must start with
an inside-out view rather than an outside-in view. Don't do it just because
there is a general buzz about things - big data, predictive modeling, digital
analytics, real-time analytics etc. What measures are we willing to impact, by
which teams within the company, how is it being aligned and therefore how can
analytics support those business decisions is when it becomes a part of the
corporate culture.

Analytics
that doesn't help a business person make a decision is wasted data. Integrate
big data into strategic decision analysis supporting corporate strategic
decision and execution to achieve sustainable profit market shares. Nowadays,
businesses are barraged with "data", but that's not equal to
information.Analytics comes in
stages. First data, then metrics - which are simply data combined to something
meaningful, then models - which predict, then decisions - which act.Any organization needs to take a
business decision through this framework step-by-step. Often, analytics
providers "jump to the end" without taking the organization through
the journey. That just creates complex, unusable analytics that get overridden
by tribal knowledge because that's what everyone understands.

Good
analytics brings meaning to the measurements, by uncovering relationships
between, inputs, effort and outputs. To be valuable, it has to do so
in the context of theory about how the system should behave. Otherwise, the
strongest correlations in the world are dangerous bases from which to make
decisions. Like any other engineering discipline, look for something in
analytics project, you could reuse before inventing from scratch; both in the
need for a systemic view of a business (data science and analytics) and the
difficulty in adopting new approaches (confirmation bias and experiential
bias).

Take an
integrated "top-down" and "bottom-up" approach: (1) Top-down: an organization needs a
vision of being a data-driven organization, which means in this context: to
maintain a single version of the truth, to constantly seek for better tools in
order to have better and faster insights. It is more of a cultural challenge,
if the technology and the implementation are good enough. And luckily, you have
reached such maturity. (2) Bottom
up: to successfully deploy quick (sometimes dirty) solutions in the
organization and to work with agents of change, spreading the word and creating
the appetite for more, and amplify the best practices & next practices.

Because businesses
that invest in Analytics projects may cost a fortune in today’s competitive
market, they need to see clearly tangible and intangible ROI in numbers and
other key parameters such as decision-making, out-hustling the competition, how
can they differentiate in the competitive landscape, Analytics should help in
elevating the firms /organizations in parameters such as Branding, Sales,
Marketing, Operational efficiencies, Customer Satisfaction, etc. If you want to
speed it up – influence by changing the culture, encouraging the demand. It
takes both leadership vision and systematic approaches in building analytics
based business capability as competitive advantage and business differentiator.